• Journal of Korea Game Society
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• v.10 no.5
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• pp.65-73
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• 2010

In this paper, we developed the device for an interactive game interface using bio signals which were able to recognize user's motion intention using EMG signals and it was applied to the games which need the information of the muscle motion directions. The module for acquiring EMG signals consists of 4-Ch, wrist-motions were defined as up, right, down and left state. The user's intent was recognized through thresholding and comparing signals of each channel. The classification result of the motion directions could control the arrow keys on the keyboard of PC and it was applied on the various games. This proposed game device can be expected to induce an effective exercise with an interesting and enjoyment, and it can use both self-developed or commercial games.

• Physical Therapy Korea
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• v.8 no.3
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• pp.11-26
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• 2001

In rehabilitation programs involving muscle re-education and endurance exercise, it is necessary to confirm when fatigue occurs. It is also necessary to quantify fatigue, to confirm whether the muscle has been exercised sufficiently. In general, as fatigue occurs, the force-generating ability of the muscle is reduced. If the median frequency (MDF) obtained from electromyogram (EMG) power spectrum is correlated highly with work, then the timing and degree of fatigue may be confirmed. This study examined the relationship between work and MDF obtained from the EMG power spectrum during repetitive isokinetic exercise. Surface EMG signals were collected from biceps brachii and vastus lateralis of 52 normal subjects (26 males, 26 females) at $120^{\circ}/sec$ and $60^{\circ}/sec$ while performing an isokinetic exercise. The exercise was finished at 25% of peak work. MDF data was obtained using a moving fast Fourier transformation (FFT), and random noise was removed using the inverse FFT, then a new MDF data was obtained from the main signal. There was a high correlation between work and MDF during repetitiv isokinetic exercise in the biceps brachii and vastus lateralis of males and the biceps brachii of females (r=.50~.77). However, there was a low correlation between work and MDF in the vastus lateralis of females (r=.06~.19).

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.2 s.302
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• pp.39-48
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• 2005

This paper proposes a novel approach to recognize nine kinds of motion for a multifunction myoelectric hand, acquiring four channel EMG signals from electrodes placed on the forearm. To analyze EMG with properties of nonstationary signal, time-frequency features are extracted by wavelet packet transform. For dimensionality reduction and nonlinear mapping of the features, we also propose a feature projection composed of PCA and SOFM. The dimensionality reduction by PCA simplifies the structure of the classifier, and reduces processing time for the pattern recognition. The nonlinear mapping by SOFM transforms the PCA-reduced features to a new feature space with high class separability. Finally a multilayer neural network is employed as the pattern classifier. From experimental results, we show that the proposed method enhances the recognition accuracy, and makes it possible to implement a real-time pattern recognition.

• Journal of the Ergonomics Society of Korea
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• v.32 no.3
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• pp.217-227
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• 2013

Objective: The purpose of this study was to analyze 'response time', 'peak response time' and 'overshoot value' for each muscle by applying the EMG signal to the vehicle response in ISO 7401 and to quantify the response of the driver according to vehicle characteristics by comparing vehicle characteristics and muscle responses of the driver. Background: The Open-loop test defined in international standards ISO 7401 is the only method for evaluating the performance of the vehicle. However, this test was focused only on mechanical responses, not driver's ones. Method: One skilled male driver(22 yrs. experience) was participated in this experiment to measure muscle activities of the driver in transient state. Then the seven muscle signals were applied to calculate 'response time', 'peak response time', and 'overshoot value'. Results: In the analyses of the EMG data, the effects of vehicle type and muscle were statistically significant on the 'response time' and 'peak response time'. Also, the effects of vehicle type, muscle, and lateral acceleration level were statistically significant on the 'overshoot value' in this study. According to the analyses of the vehicle motion data, vehicle motion variable(LatAcc, Roll, YawVel) was statistically significant on the 'response time' and vehicle type, vehicle motion variable, and lateral acceleration level were statistically significant on the 'peak response time', respectively. Conclusion: In the analyses of the 'response time' and 'overshoot value', the data of muscle activities(EMGs) was better index that could evaluate the vehicle characteristic and performance than the data of vehicle motion. In case of peak response time, both EMG and vehicle motion data were good index. Application: The EMGs data from a driver might be applicable as index for evaluation of various vehicle performances based on this study.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.6
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• pp.38-43
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• 2009

We provide a method to infer finger flexing motions using a 4-channel surface electromyogram (sEMG). Surface EMGs are harmless to the human body and easily acquired. However, they do not reflect the activity of specific nerves or muscles, unlike invasive EMGs. On the other hand, the non-invasive type is difficult to use for discriminating various motions while using only a small number of electrodes. Surface EMG data in this study were obtained from four electrodes placed around the forearm. The motions were the flexion of the thumb, index, middle, ring, and little linger. One subject was trained with these motions and another left was untrained. The maximum likelihood estimation was used to infer the finger motion. Experimental results have showed that this method could be useful for recognizing finger motions. The average accuracy was as high as 95%.

• Journal of Biomedical Engineering Research
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• v.32 no.1
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• pp.45-54
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• 2011

Cuff electrodes have a benefit for chronic electroneurogram(ENG) recording while minimizing nerve damage. However, the ENG signals are usually contaminated by electromyogram(EMG) activity from the surrounding muscle, the thermal noise generated within the source resistance, and the electric noise generated primarily at the first stage of the amplifier. This paper proposes a new cuff electrode to reduce the interference of EMG signals. An additional middle electrode was placed at the center of cuff electrode. As a result, the proposed cuff electrode achieved a higher signal-to-interference ratio compared to the conventional tripolar cuff. The cuff electrode was then assembled together with closure, headstage, and hermetic case including electronic circuits. This paper also presents a lownoise amplifier system to improve signal-to-noise ratio. The circuit was designed based on the noise analysis to minimize the electronic noise. The result shows that the total noise of the amplifier was below $1{\mu}V_{rms}$ for a cuff impedance of $1\;k{\Omega}$ and the common-mode rejection ratio was 115 dB at 1 kHz. In the current study, the performance of nerve cuff electrode system was evaluated by monitoring afferent nerve signals under mechanical stimuli in a rat animal model.

• Journal of Digital Convergence
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• v.15 no.1
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• pp.381-391
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• 2017

Biometric technology is a technology for authenticating a user using the physical or behavioral features of the inherent characteristics of the individual. With the necessity and efficiency of the technology in the fields of finance, security, access control, medical welfare, inspection, and entertainment, the service range has been expanding. Biometrics using biometric information such as fingerprints and faces have been exposed to counterfeit and disguised threats and become a social problem. Recent studies using a bio-signal from the inside of the body other than the bio-information of the external body are being developed. This paper analyzes the recent research and technology of biometric systems using bio-signals, ECG, heart sounds, EEG, and EMG to present the skills needed for the development direction. In the future, utilizing the deep learning to build and analyze database to manage bio-signal based big data for the complex condition of individuals, biometrics technologies suitable for real time environment are expected to be researched.

• Journal of Biomedical Engineering Research
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• v.20 no.3
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• pp.299-305
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• 1999

In thls paper, the representative beal textraction algorIthms for the diagnostic parameter extraction in noisy signal were compared. We used the avernge, median, mode, and trmmed mean to calculale the central tendency. In our experimenl, we have restricted to four kinds of noises -EMG noise, 60Hz powerline inlerference, ahrupl baseline shift, and baselme drift due to respimtion-which were commonly occurred in ECG mgnal, then we have calculated signal-to-noise ratios(SNRs) for the ECG corrupted with each noise and all noises together. As the result of this paper, we have proved that the average method has super lor performance than the others in the ECG corrupted wilh EMG noise. When the signal mcludes extreme value such as abrupt baseline shIft, the median, mode, trimmed mean methods have supenor performance in the SNR ratios. Especially when the ECG corrupted with baseline drift due to respirallon, the trimmed mean method was most efficient because ST level change was 0 V.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.1
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• pp.171-182
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• 2015

For fast recovery from physical discomfort and getting back to normal life, many rehabilitation treatments have been performed on patients. Computer games have been one of such treatments that are able to apply to patients effectively. However, because most of such games are locational-based, it is hard to figure out exact medical condition of patients that provide more information to medical doctors. This paper presents a rehabilitation game for patients, which is locational-based as well as rotational-based, who are having external wound or aging diseases by using electromyography signal and gyroscopic sensors. Through this game, we are able to understand how to lead the patients to involve in physical therapy more and how to obtain exact conditions of patients from the games. From several experiments, we found out that our games are able to make patients to increase their physical activity and possibility.

• Journal of Biomedical Engineering Research
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• v.16 no.2
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• pp.201-208
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• 1995

The information obtained from the analysis of respiratory muscle elecromyographic (EMG) activities provides a mean for studying muscular activity in relation to the ventilatory process. Thus, in order to comprehend the airflow pattern and its brain control, signal processing is required to characterize respiratory muscle activity. This paper presents a computerized method for the analysis of the electrical activity of the respiratory muscles of premature lambs, and focuses upon the automatic determination of respiratory timing points such as onset and cessation points of the burst activity. Based on experimental results, reliable timing points can be obtained using the proposed methodology.